Job Description

At Kibernum we are looking for a Senior Data Engineer to join a project in the banking sector, focused on the development of a modern data platform in AWS, with batch processing and streaming.

We are looking for a profile with verifiable experience in productive data pipelines, working with lakehouse technologies and event-driven architectures.

Main responsibilities
Design, develop and maintain data pipelines in AWS (batch and streaming).
Implement ingestion processes from Kafka to S3 using Glue and/or Lambda.
Build and optimize jobs in AWS Glue with PySpark.
Design and manage tables in Apache Iceberg over S3.
Implement data quality validations in pipelines.
Perform analytical queries on data (Athena/SQL).
Develop and optimize AWS Lambda functions in Python.
Build dashboards and visualizations in Amazon QuickSight.

Requirements (Exclusive)
Solid experience as a Data Engineer (senior level).
Verifiable experience in:
AWS Glue (Streaming and Batch, PySpark)
Apache Iceberg over S3
Kafka (event consumption in data pipelines)
Python
AWS Lambda
Amazon S3 (data lake)
Glue Data Catalog
Amazon QuickSight (dashboard creation)
Experience developing data pipelines in production (ETL/ELT).

It will be valued additionally
Experience in Data Quality tools (Great Expectations, Deequ or others).
Management of Athena / analytical SQL.
Experience in highly critical projects (banking, fintech, telecom).
Knowledge of modern data architectures (lakehouse, streaming).

Conditions
Permanent contract by Kibernum
100% remote mode
Supplemental health, life and dental insurance
Birth bonuses and family support
National Holiday and Christmas Bonuses
Quarterly adjustment by CPI
Corporate agreements and Kibernum benefits",